In [12]:

    

import vincent
import pandas as pd
import random

#Iterable
list_data = [10, 20, 30, 20, 15, 30, 45]

#Dicts of iterables
cat_1 = ['y1', 'y2', 'y3', 'y4']
index_1 = range(0, 21, 1)
multi_iter1 = {'index': index_1}
for cat in cat_1:
    multi_iter1[cat] = [random.randint(10, 100) for x in index_1]

cat_2 = ['y' + str(x) for x in range(0, 10, 1)]
index_2 = range(1, 21, 1)
multi_iter2 = {'index': index_2}
for cat in cat_2:
    multi_iter2[cat] = [random.randint(10, 100) for x in index_2]

#Pandas
import pandas as pd

farm_1 = {'apples': 10, 'berries': 32, 'squash': 21, 'melons': 13, 'corn': 18}
farm_2 = {'apples': 15, 'berries': 43, 'squash': 17, 'melons': 10, 'corn': 22}
farm_3 = {'apples': 6, 'berries': 24, 'squash': 22, 'melons': 16, 'corn': 30}
farm_4 = {'apples': 12, 'berries': 30, 'squash': 15, 'melons': 9, 'corn': 15}

farm_data = [farm_1, farm_2, farm_3, farm_4]
farm_index = ['Farm 1', 'Farm 2', 'Farm 3', 'Farm 4']
df_farm = pd.DataFrame(farm_data, index=farm_index)

#As DataFrames
index_3 = multi_iter2.pop('index')
df_1 = pd.DataFrame(multi_iter2, index=index_3)
df_1 = df_1.reindex(columns=sorted(df_1.columns))

cat_4 = ['Metric_' + str(x) for x in range(0, 10, 1)]
index_4 = ['Data 1', 'Data 2', 'Data 3', 'Data 4']
data_3 = {}
for cat in cat_4:
    data_3[cat] = [random.randint(10, 100) for x in index_4]
df_2 = pd.DataFrame(data_3, index=index_4)

import pandas.io.data as web
all_data = {}
for ticker in ['AAPL', 'GOOG', 'IBM', 'YHOO', 'MSFT']:
    all_data[ticker] = web.get_data_yahoo(ticker, '1/1/2010', '1/1/2013')
price = pd.DataFrame({tic: data['Adj Close']
                      for tic, data in all_data.items()})


    

In [13]:

    

import vincent
vincent.core.initialize_notebook()
bar = vincent.Bar(multi_iter1['y1'])
bar.axis_titles(x='Index', y='Value')
bar.display()


    

In [14]:

    

line = vincent.Line(multi_iter1, iter_idx='index')
line.axis_titles(x='Index', y='Value')
line.legend(title='Categories')
line.display()


    

In [15]:

    

line = vincent.Line(price[['GOOG', 'AAPL']])
line.axis_titles(x='Date', y='Price')
line.legend(title='GOOG vs AAPL')
line.display()


    

In [16]:

    

scatter = vincent.Scatter(df_1)
scatter.axis_titles(x='Index', y='Data Value')
scatter.legend(title='Categories')
scatter.colors(brew='Set3')
scatter.display()


    

In [17]:

    

stacked = vincent.StackedArea(df_1)
stacked.axis_titles(x='Index', y='Value')
stacked.legend(title='Categories')
stacked.colors(brew='Spectral')
stacked.display()


    

In [18]:

    

stacked = vincent.StackedArea(price)
stacked.axis_titles(x='Date', y='Price')
stacked.legend(title='Tech Stocks')
stacked.display()


    

In [19]:

    

stack = vincent.StackedBar(df_2)
stack.legend(title='Categories')
stack.scales['x'].padding = 0.1
stack.display()


    

In [20]:

    

stack = vincent.StackedBar(df_farm.T)
stack.axis_titles(x='Total Produce', y='Farms')
stack.legend(title='Produce Types')
stack.colors(brew='Pastel1')
stack.display()


    

In [21]:

    

group = vincent.GroupedBar(df_2)
group.legend(title='Categories')
group.colors(brew='Spectral')
group.width=750
group.display()


    

In [22]:

    

group = vincent.GroupedBar(df_farm)
group.axis_titles(x='Total Produce', y='Farms')
group.legend(title='Produce Types')
group.colors(brew='Set2')
group.display()


    

In [23]:

    

pie = vincent.Pie(farm_1)
pie.legend('Farm 1 Fruit')
pie.display()


    

In [27]:

    

donut = vincent.Pie(farm_1, inner_radius=200)
donut.colors(brew="Set2")
donut.legend('Farm 1 Fruit')
donut.display()